Overview

The book ""Artificial Intelligence in Optimization of Nanocarriers"" presents a comprehensive insight into the application of artificial intelligence (AI) in the design, development, and optimization of nanocarrier-based drug delivery systems. It explores how machine learning, deep learning, and computational modeling are transforming pharmaceutical research by improving precision, efficiency, and predictive performance in formulation design. The book emphasizes the role of AI-driven algorithms in correlating formulation parameters with therapeutic outcomes, predicting drug release profiles, and optimizing particle size, surface characteristics, and targeting efficiency. It also highlights emerging areas such as AI-assisted molecular modeling, predictive toxicology, and simulation-based formulation design. By bridging traditional pharmaceutics with intelligent automation, this volume serves as a valuable resource for researchers, academicians, and professionals in pharmacy, nanotechnology, and biomedical sciences, showcasing the transformative potential of AI in advancing personalized and precision nanomedicine.

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